WEEK 1
01 - Introduction to Algorithms
02 - Analysis of algorithms
03 - Growth of functions
04 - Asymptotic notations
WEEK 2
05 - Operations and properties of asymptotic notations
06 - Recurrences (Substitution method)
07 - Iteration method & Recursion trees
08 - Solving Recurrences (Decreasing Functions)
WEEK 3
09 - Solving recurrences (Dividing functions)
10 - The Master Method
11 - Divide and Conquer: Binary Search
12 - MAX MIN.
WEEK 4
13 - Quick Sort
14 - Merge Sort
15 - Greedy Method: Job sequencing
16 - Fractional Knapsack method
WEEK 5
17 - Huffman codes
18 - Optimal storage on tapes
19 - Dynamic programming (General method)
20 - Multistage graphs
WEEK 6
21 - Longest common subsequences
22 - Dynamic Programming (All Pairs Shortest Paths)
23 - Backtracking (General methods)
24 - N-Queens Problem
WEEK 7
25 - Sum of subsets
26 - 0/1 Knapsack problem
27 - Branch and Bound (General method)
28 - Least Cost Branch and Bound
WEEK 8
29 - Traveling salesperson problem Using LCBB
30 - Lower bound theory through reductions
31 - P, NP, NP hard and NP complete problems _ basic concepts.
32 – Approximate Algorithms
WEEK 9
33 – The set veering problem
34 - The traveling salesman problem
35 - The Vertex Cover Problem
36 - The subset sum problem
WEEK 10
37 - Parallel Algorithms, Parallelism_ PRAM and other Models
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